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PIMRC-2023

Jigyasu Khandelwal, M.S student supervised by Dr. Sachin Chaudhari presented a paper virtually on DoA Estimation using Cascaded Neural Networks and Angle Classification for Coherent Signals at  IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC-2023) held in Toronto, Canada from 5 to 8 September. 

Here is a summary of the paper as explained by the authors Jigyasu Khandelwal, M.S student; M Madhuri Latha, Ph.D scholar; Nitin Nilesh, Former M.S by research student and Dr. Sachin Chaudhari:

This paper focuses on improving Direction of Arrival (DoA) estimation for two coherent sources using a Uniform Linear Array (ULA). It is demonstrated that the DoA estimation error increases as the angle of the incoming signal moves away from the center in the range (-90◦, 90◦) for existing schemes. It introduces a Cascaded Neural Network (CaNN) with two stages of neural networks: the Enhanced SNR (ESNR) classifier and the Angle Estimator. The CaNN outperforms existing methods, particularly in low Signal-to-Noise Ratio (SNR) scenarios and for different angles, addressing the challenge of coherent signals by using a spatially smoothed auto-covariance matrix.

Conference Page: https://pimrc2023.ieee-pimrc.org/

September 2023